The focus of this study is the genetics of variation in human gene expression. Our overall goals are to characterize the extent of variation in gene expression and to identify the genetic determinants of this variation. The specific aims for this renewal application are: Aim 1. Expand materials and test for replication of linkage/association in an independent sample of families. Aim 2. Carry out family studies of differential allelic expression. Aim 3. Characterize the transcriptional regulatory regions. In the first two years of the current three-year grant, we have determined the gene expression phenotypes of members of approximately40 large families and carried out linkage analysis to determine the chromosomal location linked to each phenotype. The findings were followed up by genome-wide association analysis of the expression phenotypes, using SNP genotypes in samples from the International HapMap Project. In this renewal application, we will extend our genetic study to 45 additional families. The new phenotype data, along with SNP genotypes of the same individuals, will be used to evaluate replication of findings from the original genome-wide linkage and association analyses, and to strengthen the evidence for positive results. To complement our findings of differential allelic expression from linkage and association, we will carry out analysis of "allelic imbalance" in monozygotic twins and family members. By measuring the expression of transcripts from the two alleles of a gene, we get a direct assessment of cis-acting regulatory effects on gene expression. Results from such analyses have revealed extensive variability in the nature and extent of allelic imbalance. Our family-based approach will allow us to assess the relative contributions of inherited cis and trans regulators, and of imprinting, to this variability. Once we have identified candidate regions that contain cis- and/ or trans-acting transcriptional regulators, we will perform molecular characterization of those regions in order to identify the sequence variants responsible for the observed variation in gene expression, and determine the regulatory mechanisms. Gene expression is the link between DNA sequence and phenotype variation, including disease. Our approach will allow us to characterize gene expression variation in humans and to understand transcriptional control by identifying transcriptional regulators. The level of gene expression is also a paradigm for other quantitative traits. Therefore, the molecular and analytical approaches developed here can be generalized and applied to the study of other quantitative traits in humans, including complex genetic diseases.